def make_workspace(self, image, outline=None, labels=None):
'''Make a workspace for testing ApplyThreshold'''
m = cpmeas.Measurements()
object_set = cpo.ObjectSet()
module = O.OverlayOutlines()
module.blank_image.value = False
module.image_name.value = INPUT_IMAGE_NAME
module.output_image_name.value = OUTPUT_IMAGE_NAME
if outline is not None:
module.outlines[0].outline_name.value = OUTLINE_NAME
m.add(OUTLINE_NAME, cpi.Image(outline))
module.outlines[0].outline_choice.value = O.FROM_IMAGES
if labels is not None:
objects = cpo.Objects()
if len(labels) > 1:
ijv = np.vstack(
[np.column_stack(list(np.where(l>0)) + [l[l>0]])
for l in labels])
objects.set_ijv(ijv, shape=labels[0].shape)
else:
objects.segmented = labels[0]
object_set.add_objects(objects, OBJECTS_NAME)
module.outlines[0].outline_choice.value = O.FROM_OBJECTS
module.outlines[0].objects_name.value = OBJECTS_NAME
pipeline = cpp.Pipeline()
workspace = cpw.Workspace(pipeline, module, m, object_set, m, None)
m.add(INPUT_IMAGE_NAME, cpi.Image(image))
return workspace, module
def make_workspace(self, image, outline):
'''Make a workspace for testing ApplyThreshold'''
module = O.OverlayOutlines()
module.blank_image.value = False
module.image_name.value = INPUT_IMAGE_NAME
module.output_image_name.value = OUTPUT_IMAGE_NAME
module.outlines[0].outline_name.value = OUTLINE_NAME
pipeline = cpp.Pipeline()
object_set = cpo.ObjectSet()
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
workspace = cpw.Workspace(pipeline, module, image_set, object_set,
cpmeas.Measurements(), image_set_list)
image_set.add(OUTLINE_NAME, cpi.Image(outline))
image_set.add(INPUT_IMAGE_NAME, cpi.Image(image))
return workspace, module